{"id":1198833,"url":"https://alion.io/job/leidos-operational-energy-data-analyst","title":"Operational Energy Data Analyst","company":{"id":7791,"name":"Leidos","domain":"leidos.com","url":"https://alion.io/company/leidos","size_band":"5000+","is_staffing_agency":true,"is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":90,"open_postings":82,"ghost_share":0,"stale_share":0.61,"repost_share":0,"time_to_fill_p50_days":21,"computed_at":"2026-09-24T05:45:00Z"}},"role":"Analytics","role_family":"Analytics","seniority":"middle","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Washington, United States"],"countries":["US"],"hiring_countries":["US"],"hiring_countries_total":1,"salary":{"min":115000,"max":120000,"currency":"USD","period":"year","gross":null,"usd_annual":120000},"salary_estimate":null,"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Databricks","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Machine Learning","optional":false},{"name":"Power Automate","optional":false},{"name":"Power BI","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"Tableau","optional":false},{"name":"PyTorch","optional":true},{"name":"Spark","optional":true},{"name":"TensorFlow","optional":true}],"status":"live","first_seen_at":"2026-09-24T19:43:10Z","employer_posted_date":"2026-09-24","last_verified_at":"2026-09-24T19:43:10Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"The Leidos team supporting the Deputy Assistant Secretary of the Air Force for Operational Energy has an opening for an Operational Energy Data Analyst. Leidos supports the Deputy Assistant Secretary of the Air Force (Operational Energy) (SAF/IEN) with project management and policy support subject matter experts. Each year about $9B, or 7-8% of the Air Force budget has gone to purchase energy. Approximately 86%, or $7.2B, is operational energy (aviation fuel). The Air Force Operational Energy Program vision is to create an energy optimized Air Force that maximizes combat capability for the warfighter\nLocation: This is a remote position; however, candidates must reside in the Washington, DC metropolitan area.\nPrimary Responsibilities:\nCollaborate with the Operational Energy team to quantify the impact of prospective and current initiatives using statistical analysis, data wrangling, and predictive machine learning models.\nEstablish key performance indicators (KPIs) to track and evaluate the effectiveness of team projects and initiatives.\nDesign, build, and maintain interactive business intelligence dashboards focused on fuel consumption and aviation energy data.\nDefine and evaluate aviation energy metrics to identify and prioritize actionable energy-saving opportunities.\nAcquire and validate necessary aviation operational data, conducting quantitative analyses to recommend optimal energy-efficiency solutions.\nMaintain regular, proactive communication with cross-functional stakeholders and team liaisons.\nRequired Qualifications:\nBachelors’ degree in Data Science, Statistics, Computer Science, Engineering, or a related quantitative field, with 4+ years of data analysis experience or a Masters’ degree in Data Science, Statistics, Computer Science, Engineering, or a related quantitative field, with 3+ years of data analysis experience.\nActive DOD Secret security clearance.\nProficiency across data manipulation, analytics, and governance tools (e.g., SQL, Python, PySpark, Databricks, ETL pipelines, Power Automate, and Tableau/PowerBI/Qlik).\nProven experience designing scalable data architectures and developing rigorous statistical analytics frameworks.\nDemonstrated track record in technical writing with strong verbal and written communication skills across technical and executive audiences.\nAbility to travel as business needs require.\nPreferred Qualifications:\nFamiliarity with or direct experience supporting the Air Force Operational Energy or related DoD energy initiatives.\nHands-on experience developing data pipelines, models, or workflows within Palantir Foundry.\nDemonstrated experience developing and deploying deep learning or machine learning models using frameworks such as PyTorch or TensorFlow.\nSalary Range for this position: $115K to $120K\nIf you're looking for comfort, keep scrolling. At Leidos, we outthink, outbuild, and outpace the status quo - because the mission demands it. We're not hiring followers. We're recruiting the ones who disrupt, provoke, and refuse to fail. Step 10 is ancient history. We're already at step 30 - and moving faster than anyone else dares.\nOriginal Posting:\nSeptember 24, 2026For U.S. Positions: While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above.\nPay Range:\nPay Range $73,450.00 - $132,775.00The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.","description_format":"text","description_chars":3872,"description_truncated":false,"requirements":{"experience_years_min":4,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":true,"languages":[]},"benefits":["Equity"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":[],"lifecycle":[{"event":"open","at":"2026-09-24T19:43:10Z"}],"liveness":{"score":52,"band":"ok","label":"Likely open","p_open":1,"p_active":0.516,"p_room":1,"age_days":0,"expected_fill_days":21,"reasons":["conf:4","agency","win:early","comp:brand"],"computed_at":"2026-09-24T23:57:15Z"},"pay":{"stated_usd_annual":120000,"is_top_pay":true},"html_url":"https://alion.io/job/leidos-operational-energy-data-analyst","json_url":"https://alion.io/job/leidos-operational-energy-data-analyst.json","meta":{"generated_at":"2026-09-24T23:57:15Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":2040,"day_limit":5000,"remaining_today":2960,"minute_limit":60,"resets_at":"2026-09-25T00:00:00Z"}}}